AI systems are beginning to produce proof ideas that experts take seriously, even when final acceptance is still pending.

Print Join the Discussion View in the ACM Digital Library The mathematical reasoning performed by LLMs is fundamentally different from the rule-based symbolic methods in traditional formal reasoning.

Engineers at the University of California San Diego have developed a new way to train artificial intelligence systems to ...

The method has two main features: it evaluates how AI models reason through problems instead of just checking whether their ...

Frustrated by the AI industry’s claims of proving math results without offering transparency, a team of leading academics has ...

Do you stare at a math word problem and feel completely stuck? You're not alone. These problems mix reading comprehension ...

The president doesn’t use numbers and statistics like an adult; he uses numbers and statistics that he thinks sound good and make him feel better.

These low-floor, high-ceiling problems support differentiation, challenging all students by encouraging flexible thinking and allowing for multiple solution paths.

Four simple strategies—beginning with an image, previewing vocabulary, omitting the numbers, and offering number sets—can have a big impact on learning.

There is a tendency to imagine genius as smooth and uninterrupted. As if the great thinkers moved from one insight to the next without pause. Albert Einstein does not quite fit that picture. For all ...

GSM8K-V is a purely visual multi-image mathematical reasoning benchmark that systematically maps each GSM8K math word problem into its visual counterpart to enable a clean, within-item comparison ...

“Yoshua recently turned 57. He is three years younger than Yann. How old is Yann?” Solving such a math word problem (MWP) requires understanding the short natural language narrative describing a state ...